UPR Info is making human rights recommendations more accessible—with a little help from machine learning
HURIDOCS collaborated with UPR Info to relaunch their Database of UPR Recommendations and Voluntary Pledges with improved features.
HURIDOCS collaborated with UPR Info to relaunch their Database of UPR Recommendations and Voluntary Pledges with improved features.
Three HURIDOCS team members reflect on their recent experience working with Google.org Fellows to leverage machine learning for human rights.
Three Google.org Fellows talk about their experience over the last several months helping HURIDOCS to leverage machine learning for human rights.
The Human Rights Database is powered in part by machine learning, the result of collaboration between Plan International, HURIDOCS and Google.org fellows.
Together with some of our partner organizations and Google.org Fellows, we’re exploring how machine learning can support access to human rights law.
Metadata is a crucial when working with documents, but small non-profits often struggle with organising and analysing data due to time constraints and lack of resources.
In this discussion, we hope to bring together human rights defenders, tool developers and machine learning practitioners to share knowledge and experience.
Human rights organisations are using Uwazi to add layers of context to raw documents in order to make their collections more understandable. With machine learning, we want to further exploit Uwazi’s potential.
ICAAD is analysing sexual and gender-based violence, and Uwazi is supporting their work.
We’ll be sharing our work using machine learning to help human rights advocates sift through large document collections.